1. Field of the Invention
The present invention relates to a method and apparatus for determining "attractors" in data fields of a physical property or set of physical properties of an object.
2. Description of the Related Art
Many current methods of object exploration involve the analysis of data fields for observed physical properties of the object such as the strength of physical fields (e.g., magnetic, radioactive, gravitational, infrared, and electromagnetic) to deduce the location and range of significant features within the object. There are two principal approaches for analyzing data fields to detect significant features within the object. The first approach is pattern recognition which involves comparing a data field to other data fields representing physical properties of areas known to possess a desired significant feature. When certain patterns are common to the data fields, the presence of the desired significant feature in the survey area under investigation is indicated. The second approach is the use of an "expert system" that classifies data according to a complex scheme that employs many variables and uses decision-making rules subjectively selected by an investigator based on his own experience, knowledge, and intuition.
Unfortunately, pattern recognition methods and "expert system" technology suffer from several disadvantages. First, they are biased in that they produce outcomes that are heavily influenced by past occurrences of significant features, as in the case of pattern recognition, or by the selection criteria chosen by the investigator. As a result of such a bias, more meaningful occurrences of significant features within the data may be suppressed in favor of features that are less meaningful, but that happen to correlate with a previously observed feature or a feature predicted to be meaningful by an investigator. Second, the aforementioned methods are directive because judgments of correlation between features in the data fields are made with the target features in mind. Thus, at each opportunity for deciding whether sufficient correlation exists, incremental preferences for the predetermined target feature are introduced. Accordingly, neither method permits natural meaningful features within the data fields to be detected without the influence of a target feature selected beforehand by the investigator.